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TECH & AI
Are You ’Mass Affluent’ Not ‘Truly Rich’? Sorry, Your Wealth Manager Might Be AI Now
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Wealth managers may be ghosting their normie clients and automating the services they currently count on, according to a report from Bloomberg. The article surfaces a revealing piece of jargon used by Debasish Patnaik, a partner at the consulting firm McKinsey & Company: “mass affluent,” referring to wealth management clients with $1 million or less in liquid assets. If you are mass affluent, I hate to break the news that your wealth manager apparently never actually cared about you, and may no longer be manually compiling those reports about how things are going in your portfolio. “The mass-affluent client now gets something close to private-banking quality from AI,” Patnaik tells Bloomberg. This, according to Patnaik, changes the picture when it comes to what financial institutions need from prospective wealth managers. Meanwhile, the “truly rich,” to use Bloomberg’s term, will be getting ever more personalized service as wealth management further bifurcates into automated and ultra premium versions, according to Patnaik. The new services the job will require make a wealth manager sound like a mix between a mob consiglieri and a parent. Firms will need workers with skills like the ability to manage succession events, an understanding of “family dynamics,” the ability to decide “which family member gets to inherit what” for the masters of the universe, and the warmth necessary to “hold their hand,” when the market takes a negative turn.

Since AI can’t do any of this, Patnaik says firms will “weight hiring heavily toward it.” But your experience as part of the disgusting mass affluent rabble may soon not involve an actual wealth manager at all. Patnaik tells Bloomberg firms will need to hire for roles overseeing automation and AI software: “specialists, behavioral data scientists, personalization architects, and human-in-the-loop oversight professionals.”

Citi is on the cutting edge of this shift, Bloomberg’s story indicates. Joe Bonanno, Citi’s Head of Wealth Intelligence tells Bloomberg that his company is rolling out “AI-backed software” like a chatbot that tells clients how to manage their children’s college funds, and a push-button system that can “draft an email from the chief investment officer and distill what it means for the client.” Through all this AI, Citi apparently thinks engagement with clients will increase. Bonanno tells Bloomberg “engagement keeps clients happier and stickier.” Speaking personally, I love being happy and sticky.

But none of this may matter according to everyone’s favorite infinite-money-cheat-code-finder Elon Musk, who said in a January interview that because of AI, everything we all know about saving money is about to change. “We’re at the top of the roller coaster, and it’s about to go down,” Musk said on the podcast Moonshots with Peter Diamandis, not being totally clear about whether that’s good or bad. “Don’t worry about squirreling money away for retirement in 10 or 20 years. It won’t matter,” he told Diamandis. Whatever that means, cool, most of us aren’t successfully saving for retirement anyway. Can’t wait to see what the near future holds for rich and poor alike.



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TECH & AI
Yet Another Piece of AI-Pilled Speculative Fiction Has Gone Dangerously Viral
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Once again, AI people are letting a work of fiction seep into their brains. This time it’s a piece of speculative fiction for Europeans called “Europe 2031.” Before that, it was Citrini Research’s ”The 2028 Global Intelligence Crisis,” a story about white collar unemployment that caused stocks to dip. Before that, it was AI 2027 in which a superintelligent AI kills humanity. The sitting Vice President of the United States says he read that one. Europe 2031 was written by eight people referring to themselves as “a small group of AI researchers, think-tankers, and investors who have spent their careers at the intersection of frontier AI and European policy.” The power these documents have is not good for the world. I have some authority about this topic—a very small amount—because I wrote a book of hypothetical scenarios and managed to get it published in several countries. Speculative writing starts from some apocalyptic ending, and then the writer works backwards. This is because fiction is a cheat. You toss out reality, and only write the steps it would take to get to your destination. You can be completely upfront about what you’re doing, but readers will still think you’re predicting the future.

I told my readers not to base decisions on what I wrote, and that gaming things out is just a mental habit that helps me control my own anxiety, but people who read my hypotheticals still tell me I scared them. Worse: they ask me for advice.

My lesson is that the written word is the best medium for scaring people, and that ideas that scare people are sticky. So with that in mind, what’s scaring people now is a piece of speculative fiction about Europe not taking AI independence seriously enough. It starts as all good cheesy sci-fi should, with the kind of show-don’t-tell intro they teach you in college writing seminars: Caroline splashes cold water on her face and looks at herself in the bathroom mirror. Her hands are shaking. She grips the edge of the sink and waits for it to pass. Through the small high window she can see a slice of Washington sky, flat and bright. Oh God, what’s going to happen to poor Caroline?? Answer: She fails to convince Europe to act in time, and ends up bitter, disillusioned, and financially dependent on a billionaire friend after quitting her job. Oh, and her mom dies.

Zooming out, Europe is defenseless as AI powered hackers make mincemeat of its outdated safeguards. The European economy and probably the EU itself are looking at almost certain death after the continent is shut out of the AI race. The  two big bullies, the U.S. and China, hold all the cards. “Even in 2026, the continent could still have changed course, had it shown the courage and political will to take drastic measures,” the authors write toward the end of Europe 2031. According to the Guardian, the story has fed “a feverish discussion of the urgency for EU tech sovereignty” amid the G7 talks. Members of the European parliament have read it, and unofficial U.K.-German diplomatic talks have been informed by it. That’s frightening.

My take on speculative stories is that they are lies that can nonetheless clear away mental fog, particularly if the situation proposed is one people already talk about without much reflection on what it might take to get there. But much better writers than me have regretted parts of their speculations. For instance, Kim Stanley Robinson reportedly felt remorse after seeming to endorse crypto as part of a climate change solution in his book Ministry for the Future. Riveting talk by Kim Stanley Robinson this aft @Stanford. Says he regrets ever mentioning bitcoin/crypto in Ministry for the Future (calls it a fraudulent scam) & spoke about how we are in a very different structure of feeling on the polycrisis now than when he wrote it in 2019 pic.twitter.com/fcw6zZCa7E — Britt Wray, PhD (@brittwray) June 5, 2022   So remember, kids: stories are lies first and foremost, and should always be treated as such.



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TECH & AI
AI in Cardiac CT • LITFL • Artificial Intelligence
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Artificial intelligence (AI) is transforming cardiac CT from real-time coronary artery analysis and automated TAVI planning to detecting coronary inflammation invisible to the human eye. Panel discussion with Dr. Ronak Rajani exploring issues including AI hallucinations, accuracy, blackbox algorithms and clinician responsibility. Here we pick out a handful of highlights from a free full-length webinar on the topic.

Is AI already part of my cardiac imaging workflow?

It probably is. You just might not realise it. AI has been quietly embedded in many radiology platforms for years, handling image segmentation and generating curved multiplanar reformats in the background without revealing itself. 

Why is there such urgency around AI in cardiac imaging?

Here’s the ugly truth. Training a radiologist takes 11 years, and by 2050, roughly a quarter of the world’s population will be over 60. Demand for cardiac imaging is already outpacing the workforce, and that gap is only going to widen. In this regard, AI isn’t a luxury, it’s a practical response to a problem that isn’t going away. 

What does a fully automated cardiac CT report look like in practice?

In a live demonstration during the webinar, one platform produced a complete CCTA report with plaque analysis, calcium score, and CT-FFR included all within eight to ten minutes of the scan being performed. The clinician reviews the output, makes any edits, and approves it. It’s less of a replacement of the reporting process and more a very fast first draft that’s already done most of the heavy lifting.

If an AI tool makes a diagnostic error, who is responsible?

The question that almost all of us are thinking about. And the answer that AI companies would prefer not to advertise. Under most current legal and regulatory frameworks, the clinician retains primary responsibility for patient care, full stop. These tools are classified as decision support, not autonomous decision-makers. The AI suggests, the clinician decides.

Can AI reliably automate TAVI CT planning?

Reporting a TAVI scan is one of the most time-consuming tasks in cardiac imaging, regularly taking 30 to 40 minutes of careful manual measurement per case. AI platforms can reduce that down to a couple of minutes end-to-end, with less than one minute of clinician screen time. In terms of accuracy, they have been validated against expert measurements across more than 1,000 real-world patients and exceeded 98%.

How can cash-strapped hospitals afford expensive AI tools?

It’s a fair question, and one that was put directly to a company presenting its technology. Their answer focused on efficiency. If AI can reduce the time a clinician spends reviewing a case from several minutes to less than a minute, the same team can manage a much larger workload. In that sense, the productivity gains can help offset the cost of the technology. A second point was that hospitals may not need to carry the full financial burden alone. Other stakeholders, such as device manufacturers and industry partners who benefit from these analyses, may also have a role in supporting adoption. 

What can AI detect in a cardiac CT that the human eye cannot?

Two-thirds of major cardiac events after CCTA occur in patients without obstructive disease, a group often reassured and discharged to primary care. In a 40,000-patient UK cohort, individuals without obstructive CAD accounted for 66.3% of all major adverse cardiac events and 63.7% of cardiac deaths over a median 2.7 years.

The hidden driver of much of this risk is coronary inflammation. AI-enabled analysis of standard CCTA can now quantify coronary inflammation indirectly, by reading subtle changes in the surrounding perivascular fat. AI can transform a routine CCTA into a map of active coronary disease biology, revealing inflamed, high-risk arteries in scans that may look “low risk” on conventional visual review

Who should benefit when patient data is used to build commercial AI tools?

One view put forward in the webinar was that value generated by AI tools built on NHS patient data ought to find its way back into the NHS, potentially through revenue-sharing arrangements. Whether that ever becomes policy is another matter, but it’s a question the field is going to have to navigate.

References

Trained in medicine at the University of Szeged and developed an early interest in public health and clinical research. She now works with Medmastery as a Webinar Specialist and In-House Teacher, creating practical educational content for healthcare professionals.



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